# Inferential Statistics Flashcards

Inferential Statistics

Criterion of “TRUTH”

Validity

The percentage of people with the disease who are detected by the test

% SENSITIVITY

TP ÷ [TP + FN] x 100

% SENSITIVITY

% SENSITIVITY, higher the sensitivity the better?

ye

what does % SENSITIVITY measures?

TRUE POSITIVE

yung mga tunay na may sakit if ever

is the percentage of people with the disease who are not detected by the test, complement of sensitivity

% FALSE NEGATIVE

FN ÷ [TP + FN] x 100

% FALSE NEGATIVE

Counterpart of %sensitivity

% FALSE NEGATIVE

T or F

Higher the sensitivity, the lower the false negative

T

inversely proportional sila with %sensitivity

is the percentage of people without the disease who are correctly labelled by the test as not diseased.

% SPECIFICITY

TN ÷ [FP + TN] x 100

% SPECIFICITY

T or F

Higher the specificity the better – mababa false positive

T

is the percentage of people without the disease who are incorrectly labelled by the test as having disease, complement of specificity.

% FALSE POSITIVE

inversely proportional with %specificity

FP ÷ [FP + TN] x 100

% FALSE POSITIVE

T or F

yes to false positive and false negative

F

NO DAPAT

is defined as the likelihood that an individual with a positive test has the disease.

PREDICTIVE VALUE OF A POSITIVE TEST

TP ÷ [TP + FP] x 100

PREDICTIVE VALUE OF A POSITIVE TEST

Lahat ng positive result to get who are TRULY POSITIVE

is defined as the likelihood that a person with a negative test does not have the disease.

PREDICTIVE VALUE OF A NEGATIVE TEST

TN ÷ [FN + TN] x 1004

PREDICTIVE VALUE OF A NEGATIVE TEST

All of the negative result to get who are FALSE NEGATIVE talaga

The ratio of the chance of the test being positive if having the condition compared to the chance of testing positive if not having the condition

Positive Likelihood Ratio +LR

The ratio of the chance of the test being negative if having the condition compared to the chance of testing negative in not having the condition.

Negative Likelihood ratio -LR

if u see this card

practice the example of maam given for the Indices to Evaluate Accuracy of a Test or Diagnostic Examination

go na

Also termed as “reproducibility” or “repeatability”

Reliability

Na ulit yung test then same result = reliability – CONSISTENT

Validity = nearest to true value

Refers to the stability or consistency of information

Reliability

The extent to which similar information is supplied when measurements are performed more than once.

Reliability

T or F

A key goal in applied biostatistics is to make inferences about unknown population parameters based on sample statistics.

TRUE

what is the difference for parameter and statistics when it comes to mean, SD, and Proportion

Paramerter = Population

Statistic = Sample

this means that kung anong TESTING used for sample, and popluation yun lang din gagamiting sa parameter

There are two broad areas of statistical inference,

- Estimation
- Hypothesis Testing

The process of determining a likely value for a population parameter (e.g., the true population mean or population proportion) based on a random sample.

Estimation – APPROXIMATION

Estimation - T or F

In practice, we select a sample from the target population and use sample statistics (e.g., the sample mean or sample proportion) as estimates of the unknown parameter

T

Estimation - T or F

The sample should be representative of the population, with participants selected at random from the population.

T

alam niyo nayan very ez

Estimation - T or F

In generating estimates, it is also important to quantify the precision of estimates from different samples.

T

Estimation

Point Estimate =

Single number

e.g.: 1, 2, and 69

Estimation

Interval Estimate (Confidence Interval Estimate) =

may decimals (2 values lower and upper limit with confidence intervals)

a range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter.

Confidence Interval

Estimation - confidence interval

Because of their _ _ _ _ _ _ _ _ _ _ _ _ , it is unlikely that two samples from a particular population will yield identical confidence intervals.

Random Nature

Estimation - confidence interval: T OR F

But if you repeated your sample many times, a certain percentage of the resulting confidence intervals would contain the unknown population parameter.

T

diko parin gets to

If you see this card

go over the inferential statistics, check the estimation interval pls

There are a number of population parameters of potential interest when one is estimating health outcomes (or “endpoints”).

Parameter Estimation

Parameter Estimation

Many of the outcomes we are interested in estimating are either

continuous or dichotomous variables

, although there are other types.

Parameter Estimation

The parameters to be estimated depend not only on whether the endpoint is continuous or dichotomous, but also on the ?

number of groups being studied.

Parameter Estimation

When 2 groups are being compared what you need to establish between the groups?

- Independent (e.g., men versus women)
- Dependent (i.e., matched or paired, such as a before and after comparison).

Parameters to estimate in health-related studies

One sample - Continuos varible

Mean

Parameters to estimate in health-related studies

One sample - dichotomous variable

Proportion or Rate

yung mga prevelance,incidence rate …

Parameters to estimate in health-related studies

2 Independent Samples - Cont. Variable

Difference in MEAN

Parameters to estimate in health-related studies

2 Independents Samples - Dichoto. Variable

Difference in proportion or rates

pag 2 independent samples, lagi difference okay? okay

Parameters to estimate in health-related studies

2 Dependent, Matched Samples - Cont. Variable

Mean Difference

iba ang difference in means sa mean difference okay? okay

Confidence Intervals

Two types of estimated for each population parameter

- Point estimate
- Confidence interval (CI) estimate.

What is the difference between Cont and Dichotomous Variable?

Cont is all about MEAN, while Dicho is proportions or rate

okay? OKAY

Confidence Intervals

one first computes the point estimate from a sample?

Ye

para makuha mo Confidence intervals